Komunitas
piefed.social
For clarity sake, that’s not what’s happening here. (Don’t misunderstand this comment as defending google, I could write a book about how much they suck) The model downloaded is a LLM called Gemini Nano, and it’s used for things like “help me write”, checking if an incoming message is scam, summaries, etc. Don’t worry about it itself being a spyware. It’s not; but for argument sake, if we were to assume that it was: they already know a lot about you through their usual apps and services, and get a lot more info out of you through them. This LLM would hardly move that needle. The actual issue is that they download it for everyone, even if their devices don’t match the minimum requirements. And without consent. And to enable it, you need to go through several menus, as the default behaviour is to use the cloud (this could change eventually, my understanding is that in this update they’re just laying the foundation) But, it’s Google that we’re talking about. Last year they were sentenced to pay a fine for spying on users despite them having their tracking settings off. And it wasn’t the first time iirc. This kind of behaviour is par for the course with them
Komunitas
lemmy.world
This article is taking advantage of the fact that most people don’t know how their software works and framing non-issues so that they sound outrageous because that draws clicks and advertising money. Most people haven’t heard of most changes made to their browser, even when those changes massively change the Browser (like Manifest v3). Yes, they could run in-browser announcements for all of these changes but it would just annoy people who don’t care anyway. Nobody wants to see a pop-up every time there’s a browser update full of information that they don’t care about. This specific change is no different than the multitude of other large changes that get implemented every update. It’s announced far ahead of time (2 years in this case), they have preview builds available for anyone to try, they run advertisements (I’ve seen Google Gemini advertisements before YT videos, for example), they publish documentation. Like every major change to Chrome, most people don’t care and don’t want to be bothered by it… that’s why they didn’t know about this specific change. Perfectly normal because, as you have said, most people are not developers or computer people so the information is not relevant to them. However, that is a hugely different scenario than the way these articles are presenting this information. They’re implying that there is something sinister or secretive about this specific update when the reality is that this information is announced and advertised like every other update that nobody cares to look at. People didn’t know it was happening because they didn’t look, not because Google was doing anything different. The articles also frame boring technical details in the most breathless way possible. For example: Hanff focuses on the environmental angle. He calculated that if this model were pushed to just 1 billion Chrome users (roughly 30% of Chrome’s user base), the distribution alone would consume 240 gigawatt-hours of energy and generate 60,000 tons of CO2 equivalent. That’s not including actually using the model, just the downloads. That sounds crazy and even if the numbers are correct (which nobody can check because how ‘he calculated’ is never explained) they’re describing a 4GB file transfer and multiplying. It’s 4GB, that’s 10% of a Netflix movie. Describing it with such framing is disingenuous outrage bait. Here’s another boring technical detail that’s framed in the same outrageous manner: What happened to asking for permission? Pretending to be outraged because they were not asked before an update was applied. Chrome, Windows, Apple’s software, etc all use automatic updates. If the author wanted to to have their permission asked for every update, that’s completely possible and has been since Chrome was first released. Nobody wants 30 different applications asking permission and providing patch notes and so the default is that updates are applied automatically. They had decades to learn about and disable automatic updates. It’s only suddenly a problem when the author needs to farm outrage. And when I remove it, I want it gone permanently—not automatic reinstallation. The author is using a browser with the AI features enabled, they go and delete a file required for that feature and then act outraged that it gets put back in place. The reason that it’s automatically re-installed is because they have the feature enabled in their browser options and Chrome repairs itself when it starts up, that includes re-downloading missing files. The AI feature is enabled and a required file is missing so it re-downloads it. Most people don’t understand how Chrome works under the hood, and that’s understandable. However, the person writing the article and the security researcher who ‘discovered’ this certainly know. They are exploiting people’s ignorance to frame completely normal processes as if they’re something to be outraged about. It’s misinformation using outrage to sell advertisement. It isn’t informing people of anything, it is experts who know better that are deliberately manipulating people for profit. This is a very common tactic in Technical Support Scams. If you’re on Windows and you open the command prompt and type ‘netstat’ you will see a scary looking list of IP addresses. One of the columns says ‘FOREIGN ADDRESS’. Tech support scammers will tell people that the foreign address means that people outside the country are connecting to their computer because they have malware and so they need to pay the scammer to fix it. Obviously that’s nonsense, as any person with the most basic professional understanding of technology will tell you. A foreign address in this context is simply the ip address of some other computer that you’re connected to for various reasons. But a person who doesn’t know much about computers can be easily fooled by someone misrepresenting this basic technical detail and it happens constantly. That’s what this article is doing.
Komunitas
lemmy.ca
It’s much more likely to be like internet fiber. Some was needed/used. datacenters will always leverage scale, and AI is only economic at 16+ concurrent users. delivers 3x the tokens/s of a single user. Current rental rates for H200s are below their runcosts. Capacity is already too high in US. Innovations for smaller, faster, cheaper models are providing significant value for less hardware. Gemini flash 3.5 is very small and fast, at much lower cost as top 2 US labs. Deepseek v4 has massive cost reductions that will filter down to rest on industry, especially for context compression which is what allows more users on a single GPU cluster. Qwen 3.6 does bring size down enough to run 3-4 month old state of the art models on consumer hardware, but again multi user service at (pro instead of industrial) 96gb ram. MTP and Turboquant are other technologies that increase tps delivery at less ram. Software stacks making better use of GPUs is eating token demand growth by itself even as exaggerated capacity comes online at slower pace than hardware investment values justified.
Komunitas
lemmy.blahaj.zone
Meh. I converted my blog from WordPress to a static site generator using Gemini’s version of Markdown as the base format, and then hosted both HTTP and Gemini versions. I later took down the Gemini version. The web site remains as static HTML driven by (a variation of) Markdown. No cookies, no JS, limited CSS. Even took out some old YouTube
Komunitas
lemmy.world
Note that sometimes Ai models check if code works by executing it. For example gemini can python function and execute it to write down the results
Komunitas
lemmy.world
A big one for me is choice of apps. Only apps made for Android Auto are available, and that’s not a lot. Especially pretty much nothing from F-Droid. Open source apps for Android Auto are very limited. Sideloading is not a thing for Android Auto either. So I can’t even choose to work around the limitations as I can on the phone itself. The ancient Android Assistant sucks. It constantly doesn’t understand what I ask it and so far I haven’t figured out when exactly it can do a google search for me and when not. Especially considering how far LLMs have come in terms of answering simple questions (e.g. if a name comes up in a podcast and I want to know a little bit of background information to that person). And when they finally add LLM support it will be Gemini only with no choice past that. Then there’s stupid design decisions in apps, e.g. that Google Maps doesn’t show GPS speed when in Android Auto mode. I also hate that Google Maps decided in an update a year or so ago that speed camera warnings (which are illegal in some of the countries I frequently drive in) can not only not be disabled but are so important that they need to take up half the screen and hide the navigation directions while they are up. This is especially crappy when I come up to a busy highway intersection where I have to get off and suddenly there’s no navigation on my screen but a stupid warning I don’t care about because I obey speedlimits anyway. And lastly (that’s likely down to the implementation in my car or my phone), there’s constant connection issues.
Komunitas
feddit.online
I asked Gemini Pro whether the thorn character messes an LLM up? If anyone is interested, here’s the answer. The short answer is it makes it harder for humans to read the text, but LLMs are not bothered by it. So, those who are using the thorn character for “th” believing that it breaks AI are not achieving anything and are just being annoying. Gemini Pro’s response: (Note that as I write this in PieFed, the thorn character is being converted to “th” and so you will have to convert it back in your brain. The belief that using the character “þ” (Thorn) “messes with” LLM training has gained some traction in privacy-focused and “anti-AI” circles. Here is a breakdown of the technical reality behind that claim. The Theory: Disrupting Tokenization Large Language Models don’t read words; they read tokens (numerical representations of character clusters). Common Tokens: In standard English, the word “the” is one of the most common tokens. It is highly optimized, and the model “understands” it perfectly. The “Thorn” Hack: If you replace “the” with “e,” you force the model’s tokenizer to handle a rare character. Because is uncommon in English training data, the tokenizer might break “e” into two separate, rare tokens (the byte for and the letter “e”). Proponents believe this makes the text “invisible” or “garbage” to the model, preventing it from learning from the content or correctly categorizing it.
Does it actually work? (Mostly No) While the idea is clever, it is generally ineffective against modern, high-scale LLMs for several reasons: Multilingual Training: Most modern models are trained on massive multilingual datasets. Icelandic uses as a standard letter. Therefore, the models already have in their vocabulary and have seen it millions of times. Byte-Level Tokenization: Modern tokenizers (using Byte Pair Encoding or BPE) are designed to handle any Unicode character by falling back to its raw bytes. They don’t “break” when they see an unfamiliar symbol; they just process it as a less-common sequence. Contextual Mapping: LLMs are excellent at pattern recognition. If a model sees a sentence like “e cat sat on e mat,” it can easily infer from the context that “e” serves the exact same linguistic function as “the.” The “Glitch Token” Phenomenon There is a grain of truth to the “glitching” idea. **In the past, ** certain rare characters or specific strings (often called “glitch tokens”) were included in a model’s vocabulary but appeared so rarely in the training data that their “embedding” (the model’s understanding of them) was never properly trained. When a model encounters a true glitch token, it can sometimes “hallucinate” or produce nonsensical output. However, is a standard UTF-8 character and is too common globally to act as a true glitch token for most general-purpose models. Summary Using is more of a digital protest or a linguistic “speed bump” than a functional way to break an AI. It might make your text harder for a simple keyword-search bot to find, but for a modern LLM, it’s just a slightly “noisy” version of English that we can still read and understand quite easily.
Komunitas
lemmy.world
When I swapped, Gemini wasn’t being shoved down our throats.
Komunitas
palaver.p3x.de
Phones, sure. I -personally- think it’s massively problematic how the phone operating system ecosystem is basically a monopoly of two companies. And I almost can’t do my paperwork or get a doctor’s appointment or train ticket anymore without accepting to forward my personal information to a list of 40 “partner” companies, a good chunk of them abroad in the USA. And then it’s massively complicated and I need 3 authenticator apps, and they do device verification and SafetyNet to make sure my(?) phone isn’t controlled by me, but Google. So yes, in reality it’s not how I envision it to be. Phones just do what Google wants them to do and that certainly also includes Gemini AI. All of this is almost impossible to avoid, and it’s getting harder each day. It certainly is that way. (Same with edge-cases in general. I had to contact modern customer support lately, and that just got way worse than it already was before AI chatbots. We just don’t do edge-cases any more. Everyone needs to get in line, have the same life and same common issues or they’re screwed.) With Linux, I doubt it. Traditionally it’s a lot about choice. Caters to its user group who (on the desktop) include a good amount of privacy advocates, people with older computers, nerds… I think we’d need some paradigm shift first. Before any of the larger distributions change their defaults. I like to believe we’re relatively safe here. And my biggest issue isn’t AI in itself, but how large, annoying companies shove it down our throats. And that’s really not how Linux works. I’ve been pondering productivity as well. I once did some AI assisted coding. Took notes and did a similar task after that the old-school way. In that case AI had wasted time, I was faster without. But it’s been a while and AI tools have improved in the last months. So I probably should repeat that experiment. And do it a couple times to get some solid numbers. I find it hard to apply it the exact right way, though. It’d underperform (on me) if I don’t get the prompt right, feed it the right amount of context if there’s a pre-existing project… It’s better at some tasks and not so good at other ones… So with the current state of technology it’s not that straightforward to delegate stuff to AI, and it’d just increase productivity. At least that’s been my previous experience. But we get a plethora of contradicting and weird reports on AI’s performance when used for coding.
Komunitas
lemmy.zip
I honestly don’t really use it, but I am excited about it in the future. :) I installed it because of OSNews, my favorite tech news website. But the Gemini page seems to be down? https://www.osnews.com/story/136770/osnews-launches-gemini-capsule/